Households That Make Less then $20k in America π΅
If Puerto Rico was a state, it would be by far the poorest in America. Significant poverty continues to exist in the south, indeed the most impoverished states are Mississippi, West Virginia, Louisiana, New Mexico and Alabama according to the 2020 American Community Survey 5 year averages.
State | Households Making Under 20k |
Puerto Rico | 48.2 |
Mississippi | 22.6 |
West Virginia | 20.6 |
Louisiana | 20.1 |
New Mexico | 19.6 |
Alabama | 19.3 |
Arkansas | 18.9 |
Kentucky | 18.8 |
South Carolina | 17.0 |
Tennessee | 16.6 |
Oklahoma | 16.2 |
North Carolina | 15.8 |
Ohio | 15.6 |
Georgia | 15.2 |
Missouri | 15.2 |
District of Columbia | 15.2 |
Montana | 15.1 |
New York | 15.0 |
Maine | 15.0 |
Michigan | 14.9 |
Florida | 14.9 |
Rhode Island | 14.6 |
Indiana | 14.6 |
Pennsylvania | 14.2 |
Texas | 13.9 |
Arizona | 13.7 |
Vermont | 13.7 |
Illinois | 13.7 |
Kansas | 13.6 |
North Dakota | 13.5 |
South Dakota | 13.5 |
Iowa | 13.4 |
Nevada | 13.4 |
Idaho | 13.3 |
Oregon | 13.1 |
Wyoming | 13.0 |
Wisconsin | 12.9 |
Nebraska | 12.7 |
Massachusetts | 12.5 |
California | 11.9 |
Delaware | 11.7 |
Connecticut | 11.6 |
Virginia | 11.3 |
New Jersey | 11.0 |
Minnesota | 10.9 |
Colorado | 10.8 |
Washington | 10.6 |
Hawaii | 10.0 |
Maryland | 10.0 |
New Hampshire | 9.9 |
Alaska | 9.9 |
Utah | 9.2 |
Here is the R code for making these statistics:
library(tidycensus)
income <- get_acs(
geography = “state”,
table = ‘B19001’,
year = 2020,
output = ‘wide’,
survey = “acs5”,
geometry = F);
perincome <- income %>% select(ends_with(‘E’), -ends_with(‘001E’)) %>%
rowwise() %>% mutate(total = sum(across(matches(‘dE’)))) %>%
mutate(across(matches(‘dE’), ~(./total)*100 )) %>% select(-total)
perincome %>% rowwise %>% mutate(under20k = sum(across(c(B19001_002E, B19001_003E, B19001_004E)))) %>% select(NAME, under20k) %>% arrange(-under20k) %>% write_csv(‘/tmp/hhunder20k.csv’)